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外显子组测序在350770人中确定了与社会经济地位相关的基因。

Exome sequencing identifies genes for socioeconomic status in 350,770 individuals.

作者信息

Wu Xin-Rui, Yang Liu, Wu Bang-Sheng, Liu Wei-Shi, Deng Yue-Ting, Kang Ju-Jiao, Dong Qiang, Sahakian Barbara J, Feng Jian-Feng, Cheng Wei, Yu Jin-Tai

机构信息

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai 200040, China.

State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai 200040, China.

出版信息

Proc Natl Acad Sci U S A. 2025 Jan 14;122(2):e2414018122. doi: 10.1073/pnas.2414018122. Epub 2025 Jan 7.

Abstract

Socioeconomic status (SES) is a critical factor in determining health outcomes and is influenced by genetic and environmental factors. However, our understanding of the genetic structure of SES remains incomplete. Here, we conducted a large-scale exome study of SES markers (household income, occupational status, educational attainment, and social deprivation) in 350,770 individuals. For rare coding variants, we identified 56 significant associations by gene-based collapsing tests, unveiling 7 additional SES-associated genes (, , , , , and ). Exome-wide single common variant analysis revealed nine lead single-nucleotide polymorphisms (SNPs) associated with household income and 34 lead SNPs associated with EduYears, replicating previous GWAS findings. The gene-environment correlations had a substantial impact on the genetic associations with SES, as indicated by the significantly increased values in several associations after controlling for geographic regions. Furthermore, we observed the pleiotropic effects of SES-associated genetic factors on a wide range of health outcomes, such as cognitive function, psychosocial status, and diabetes. This study highlights the contribution of coding variants to SES and their associations with health phenotypes.

摘要

社会经济地位(SES)是决定健康结果的关键因素,且受到遗传和环境因素的影响。然而,我们对SES遗传结构的理解仍不完整。在此,我们对350770名个体的SES标志物(家庭收入、职业地位、教育程度和社会剥夺)进行了大规模外显子组研究。对于罕见编码变异,我们通过基于基因的合并检验确定了56个显著关联,发现了另外7个与SES相关的基因(、、、、、和)。全外显子组单常见变异分析揭示了9个与家庭收入相关的主要单核苷酸多态性(SNP)和34个与受教育年限相关的主要SNP,重复了先前全基因组关联研究(GWAS)的结果。在控制地理区域后,几个关联中显著增加的值表明,基因 - 环境相关性对与SES的遗传关联有重大影响。此外,我们观察到与SES相关的遗传因素对广泛的健康结果具有多效性影响,如认知功能、心理社会状态和糖尿病。这项研究突出了编码变异对SES的贡献及其与健康表型的关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40dc/11745334/0dfa655371e4/pnas.2414018122fig01.jpg

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